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250927s2025 xx |||||o 00| ||eng c |
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|a 10.1002/adma.202510635
|2 doi
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|a pubmed25n1582.xml
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|a (DE-627)NLM393249557
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|a (NLM)41013963
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Kim, Sungho
|e verfasserin
|4 aut
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|a Spatiotemporal Reservoir Computing with a Reconfigurable Multifunctional Memristor Array
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|c 2025
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Revised 27.09.2025
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|a published: Print-Electronic
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|a Citation Status Publisher
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|a © 2025 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.
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|a The existing physical implementations of reservoir computing are constrained mainly by time-delay architectures that lack capabilities for spatial data processing. This study presents a multifunctional memristor-based reservoir computing system, the memristive echo state network (MESN), which enables spatiotemporal computation within a single device crossbar array. Utilizing a reconfigurable Ta/HfO2/RuO2 memristor, three distinct switching modes are realized: stochastic for input masking, bistable for sigmoidal activation, and analog for precise readout. A full in-memory implementation is experimentally demonstrated using a one-transistor-one-resistor crossbar array integrated with indium oxide thin-film transistors. Spatial inference is validated through cellular automata, confirming reliable hardware operation. High-level simulations based on the hardware results demonstrate the performance of the proposed MESN, achieving high accuracy in predicting the Lorenz attractor and classifying attention-deficit/hyperactivity disorder. The system also predicted the Kuramoto-Sivashinsky equation, representing the first memristor-based reservoir to model complex spatiotemporal partial differential equations. These results highlight the potential of multifunctional memristor arrays for scalable in-memory spatiotemporal computing
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|a Journal Article
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|a in‐memory computing
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|a memristive crossbar array
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|a multifunctional memristor
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|a reservoir computing
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| 650 |
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|a spatiotemporal reservoir
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| 700 |
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|a Shin, Dong Hoon
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Choi, Wonho
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Cheong, Sunwoo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Shim, Sung Keun
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Lee, Soo Hyung
|e verfasserin
|4 aut
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| 700 |
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|a Han, Janguk
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Jang, Yoon Ho
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Son, Kunhee
|e verfasserin
|4 aut
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| 700 |
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|a Ghenzi, Néstor
|e verfasserin
|4 aut
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| 700 |
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|a Hwang, Cheol Seong
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Advanced materials (Deerfield Beach, Fla.)
|d 1998
|g (2025) vom: 26. Sept., Seite e10635
|w (DE-627)NLM098206397
|x 1521-4095
|7 nnas
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| 773 |
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|g year:2025
|g day:26
|g month:09
|g pages:e10635
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|u http://dx.doi.org/10.1002/adma.202510635
|3 Volltext
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